The ROC curves for 2-folds, 4-folds, 10-folds, and leave one subject out cross validation experiments.</p
ROC curve (receiver operating characteristic curve) and area under curves (AUCs) of the validation c...
<p>(A) Results when validating against the neutral control set. (B) Results when validating against ...
<p>The ROC curves for evaluating the quality of the algorithms over the entire test datasets.</p
<p>The ROC curves based on three methods/models (TILoR: Blue line; GLM: Red line; random forest: Gre...
<p>ROC curves of different encoding SVM models using a 10-fold cross-validation.</p
<p>The ROC curves of the RF and SVM in internal five-fold cross validation for (a) Model I, (b) Mode...
<p>ROC curves of different encoding SVM models using a leave-one-out cross-validation.</p
<p>ROC curves for the two models of the development set using leave-one-out cross-validation (LOOCV)...
<p>ROC curves for the three experimental settings (Multi-instance Learning, Multi-instance Learning ...
(a) The result of the first fold PR curve. (b) The result of the second fold PR curve. (c) The resul...
<p>The ROC curve for leave-one-out cross validation and the AUC of our algorithm is 0.7645.</p
<p>The ROC curves of the RF and SVM in four independent external validations for (a) Model I, (b) Mo...
<p>ROC curves for the best result in Experiment 4 (Non correlated features at 97%).</p
<p>ROC curves obtained with different feature sets extracted from the tumor region using (a) leave-o...
<p>ROC curves of the single SVM models trained using various features based on five-fold cross-valid...
ROC curve (receiver operating characteristic curve) and area under curves (AUCs) of the validation c...
<p>(A) Results when validating against the neutral control set. (B) Results when validating against ...
<p>The ROC curves for evaluating the quality of the algorithms over the entire test datasets.</p
<p>The ROC curves based on three methods/models (TILoR: Blue line; GLM: Red line; random forest: Gre...
<p>ROC curves of different encoding SVM models using a 10-fold cross-validation.</p
<p>The ROC curves of the RF and SVM in internal five-fold cross validation for (a) Model I, (b) Mode...
<p>ROC curves of different encoding SVM models using a leave-one-out cross-validation.</p
<p>ROC curves for the two models of the development set using leave-one-out cross-validation (LOOCV)...
<p>ROC curves for the three experimental settings (Multi-instance Learning, Multi-instance Learning ...
(a) The result of the first fold PR curve. (b) The result of the second fold PR curve. (c) The resul...
<p>The ROC curve for leave-one-out cross validation and the AUC of our algorithm is 0.7645.</p
<p>The ROC curves of the RF and SVM in four independent external validations for (a) Model I, (b) Mo...
<p>ROC curves for the best result in Experiment 4 (Non correlated features at 97%).</p
<p>ROC curves obtained with different feature sets extracted from the tumor region using (a) leave-o...
<p>ROC curves of the single SVM models trained using various features based on five-fold cross-valid...
ROC curve (receiver operating characteristic curve) and area under curves (AUCs) of the validation c...
<p>(A) Results when validating against the neutral control set. (B) Results when validating against ...
<p>The ROC curves for evaluating the quality of the algorithms over the entire test datasets.</p